Acala Swap Performance Summary

Active Users
Swap Trades
Trades Per User
Trading Volume
Count U_Growth U_Trend S_Growth S_Trend TPU_Growth TPU_Trend V_Growth V_Trend
ALL 20562 1.22 0 1 0
ACA:AUSD 8896 1.11 1.21 1.08 1.06
AUSD:LCDOT 4779 1.36 0 0.94 0
DOT:LCDOT 4678 1.26 0 0.99 0
AUSD:LDOT 2209 1.05 1.07 1.01 1.7

Last updated: 2022-06-11 20:08:24

Date range of data: 2022-05-29T00:03:06.427 to 2022-06-12T00:01:36.409.

Sources:

Swaps:

Loans:

---
title: "Acala / Karura Dashboards"
output:
  flexdashboard::flex_dashboard:
    orientation: rows
    vertical_layout: scroll
    social: menu
    source_code: embed
params:
  network: Karura
  window: 14
---

```{css custom1, echo=FALSE}
.dataTables_scrollBody {
    max-height: 100% !important;
}
```

```{r global, include=FALSE}

knitr::opts_chunk$set(
  message = FALSE,
  warning = FALSE,
  comment = "#>"
)

library(kableExtra)
library(formattable)
library(lubridate)
library(flexdashboard)
library(DT)

# Helper function to concat
`%+%` <- function(a, b) paste0(a, b)

# remotes::install_github("ropensci/ghql") # if package is not already installed
library(jsonlite)
library(data.table)
library(subscanr)
library(ghql)
x <- GraphqlClient$new()

window <- params$window
endpoint <- params$endpoint
network <- params$network

# queries ####
dailyLoanCollateral <- getLoansDailyCollateral_acala_loan(network, window)
dailyLoanPositions <- getLoansDailyPositions_acala_loan(network, window)
collaterParams <- getLoansCollateralParams_acala_loan(network)
liquidity <- getLiquidity_acala(network, window)
liquidity[, volumeUSD := as.numeric(volumeUSD) / 1e18]
liq <- liquidity[, .(date, pair, type, volumeUSD)]
liq2 <- liq[, .(.N, sum(volumeUSD)), by = .(pair, date, type)]
setnames(liq2, c("date","N","V2"), c("Date","Observations","volumeUSD"))
liq2[type == 'removeLiquidity', volumeUSD := -volumeUSD]


liq <- liq[, .(.N, sum(volumeUSD)), by = .(date, type)]
setnames(liq, c("date","N","V2"), c("Date","Observations","volumeUSD"))
liq[type == 'removeLiquidity', volumeUSD := -volumeUSD]

# swaps2 <- getSwapsByDay(swap_endpoint, window)
swaps2 <- getDailyPools_acala_dex(network, window)
swaps <- getSwaps_acala_dex(network, window)
# swaps <- getSwaps(official_endpoint, window)
# swaps[, volumeUSDFloat := as.numeric(volumeUSD)]
# swaps[volumeUSDFloat < 0]
# swaps[volumeUSDFloat < 0, id]

swaps <- merge(swaps, subscanr::tokens, by.x='token0', by.y='Token', allow.cartesian=TRUE) %>% setnames("decimals","decimals0")
swaps[, Name := NULL]
swaps <- merge(swaps, subscanr::tokens, by.x='token1', by.y='Token', allow.cartesian=TRUE) %>% setnames("decimals","decimals1")
swaps[, Name := NULL]

swaps[, adj0 := as.numeric(substr(as.character(1e20),1, as.numeric(decimals0) + 1))]
swaps[, adj1 := as.numeric(substr(as.character(1e20),1, as.numeric(decimals1) + 1))]

swaps[, token0InAmount := as.numeric(token0InAmount)]
swaps[, token1OutAmount := as.numeric(token1OutAmount)]
swaps[, price0 := as.numeric(price0) / 1e18]
swaps[, price1 := as.numeric(price1) / 1e18]

swaps[, amount0 := token0InAmount / adj0]
swaps[, amount1 := token1OutAmount / adj1]

swaps[, token0 := subscanr::fixToken(token0)]
swaps[, token1 := subscanr::fixToken(token1)]
swaps[, tradePath := subscanr::fixToken(tradePath)]
swaps[, pathLength := length(strsplit(tradePath, ",")[[1]]) - 1, by = id]

swaps[, volume0USD := amount0 * price0]
swaps[, volume1USD := amount1 * price1]
swaps[, volumeUSDFloat := (volume0USD + volume1USD) / 2]
swaps[volume0USD == 0 & volume1USD > 0, volumeUSDFloat := volume1USD]
swaps[volume1USD == 0 & volume0USD > 0, volumeUSDFloat := volume0USD]

mysort <- function(a, b) ifelse(a < b, a %+% ":" %+% b, b %+% ":" %+% a)

getPath <- function(tradePath) {
  # tradePath <- swaps[1]$tradePath
  tp <- strsplit(tradePath, ",")[[1]]
  n <- length(tp) - 1
  if (n == 3) {
    return(list(mysort(tp[1],tp[2]), mysort(tp[2],tp[3]), mysort(tp[3],tp[4])))
  } else if (n == 2) {
    return(list(mysort(tp[1],tp[2]), mysort(tp[2],tp[3]), "NA:NA"))
  } 
  list(mysort(tp[1],tp[2]), "NA:NA", "NA:NA")
}
swaps[, c("pair1", "pair2", "pair3") := getPath(tradePath), by = id]

swaps[, fee := volumeUSDFloat * .03]
swaps[, feeAdj := volumeUSDFloat * .03 * pathLength]
setnames(swaps, "address", "accountId")

pairs <- rbind(swaps[exclude == FALSE, .N, by = pair1] %>% setnames("pair1", "Pair"),
              swaps[exclude == FALSE, .N, by = pair2] %>% setnames("pair2", "Pair"),
              swaps[exclude == FALSE, .N, by = pair3] %>% setnames("pair3", "Pair"))
pairs <- pairs[, sum(N), by = Pair]
# remove pairs with NA in them
pairs <- pairs[-grep("NA", pairs$Pair)]
pairs <- rbind(data.table(Pair = "ALL", V1 = sum(pairs$V1)), pairs)
pairs <- pairs[order(V1, decreasing = TRUE)] %>%
  setnames(c("Pair", "Observations"))


tvl <- swaps2[date == max(date)]
stable_dex_pool_size <- tvl[grep("USD", tvl$pair), sum(abs(tvlUSD))]

# Calculate measures for each pair
user_status   <- list()
trades_status <- list()
tpu_status    <- list()
volume_status <- list()

users_list  <- list()
trades_list <- list()
per_list    <- list()
volume_list <- list()

# remove old params object before calling render with new params list
rm(params)
for (p in pairs$Pair) {
  # p <- pairs$Pair[1]
  
  try(rm(u_list, t_list, p_list, v_list), silent = TRUE)
  
  outname <- "~/R_HOME/websites/web_acala/content/swap_" %+% network %+% "_" %+% p %+% ".html"
  unlink(outname)
  # Create report for each pair
  rmarkdown::render("~/R_HOME/karura-reports/Swap_template.Rmd",
                  output_file = outname,
                  params = list(pair = p))
  
  # Store the data for the table
  user_status[p]   <- activeUsersStatus
  trades_status[p] <- tradesStatus
  tpu_status[p]    <- avgTradeStatus
  volume_status[p] <- tradeVolumeStatus
  
  users_list[[p]]  <- u_list
  trades_list[[p]] <- t_list
  per_list[[p]]    <- p_list
  volume_list[[p]] <- v_list

}

  d <- list()
  for (x in pairs$Pair) {
    d[x] <- paste0('', x, '', collapse = '')
  }

  inline_plot <- data.frame(Count = pairs$Observations, 
                            U_Growth = unlist(user_status),
                            U_Trend = "",
                            S_Growth = unlist(trades_status),
                            S_Trend = "",
                            TPU_Growth = unlist(tpu_status),
                            TPU_Trend = "",
                            V_Growth = unlist(volume_status),
                            V_Trend = "")
  row.names(inline_plot) <- unlist(d)

  getSpecColor <- function(x) {
    x[is.na(x)] <- 0
    ifelse(x < 1, "red", "green")
  }
  
  inline_plot$U_Growth <- cell_spec(inline_plot$U_Growth, color = getSpecColor(inline_plot$U_Growth))

  inline_plot$S_Growth <- cell_spec(inline_plot$S_Growth, color = getSpecColor(inline_plot$S_Growth))
  
  inline_plot$TPU_Growth <- cell_spec(inline_plot$TPU_Growth, color = getSpecColor(inline_plot$TPU_Growth))

  inline_plot$V_Growth <- cell_spec(inline_plot$V_Growth, color = getSpecColor(inline_plot$V_Growth))

  p <- inline_plot %>%
    kbl(booktabs = TRUE, escape = FALSE, align='rrrrrrrrr') %>%
    add_header_above(c(" " = 1, " " = 1, "Active Users" = 2, "Swap Trades" = 2, "Trades Per User" = 2, "Trading Volume" = 2)) %>%  
    kable_paper(full_width = FALSE) %>%
    column_spec(4, image = spec_plot(users_list, same_lim = FALSE)) %>%
    column_spec(6, image = spec_plot(trades_list, same_lim = FALSE)) %>%
    column_spec(8, image = spec_plot(per_list, same_lim = FALSE)) %>%
    column_spec(10, image = spec_plot(volume_list, same_lim = FALSE))

```

### `r network` Swap Performance Summary

```{r plot_acala, result='asis', out.height = 12}
p

```

Last updated: `r Sys.time()`

Date range of data: `r min(swaps$timestamp)` to `r max(swaps$timestamp)`.

Sources: 

* [SubQuery Network](https://explorer.subquery.network/)

Swaps:

* [Acala Dex Data](https://explorer.subquery.network/subquery/AcalaNetwork/acala-dex)

* [Karura Dex Data](https://explorer.subquery.network/subquery/AcalaNetwork/acala-dex)

Loans:

* [Acala Loan Data](https://explorer.subquery.network/subquery/AcalaNetwork/acala-loans)

* [Karura Loan Data](https://explorer.subquery.network/subquery/AcalaNetwork/karura-loan)